bioRxivPlant BiologyPreprint
Drought reshapes enhancer-like nascent transcription and gene regulation in Oryza sativa
Fabian Ortner-Krause, Marina Goliasse, John Gitau, Aurore Johary, Farzaneh Rahmdani, Zoé Joly‐LopeziD
Abstract
Drought increasingly constrains global rice productivity, yet how water deficit remodels cis-regulatory activity in plants remains poorly resolved. Here we used precision run-on sequencing (PRO-seq) to profile nascent transcription in rice leaves under well-watered and drought conditions and mapped transcription-initiation regions with the tool dREG, which detects genome-wide peaks of bidirectional transcription displaying active-enhancer behaviour. PRO-seq captured a robust drought response at genes and revealed extensive remodelling of initiation landscapes. We detected 85,764 consensus dREG sites, of which 17,193 changed significantly under drought and were predominantly intergenic. Because plant intergenic space is rich in transposable elements and silencing-associated transcription, we integrated transposable-element overlap and small-RNA loci with chromatin accessibility and DNA methylation to prioritize 2,428 drought-responsive intergenic sites (841 induced and 1,308 repressed) that are accessible, locally hypomethylated, and bidirectionally transcribed - features consistent with enhancer-like elements. Activity at proximal candidates correlated with elevated nascent transcription of nearby genes, and a subset overlapped gene-connected chromatin loop anchors, supporting candidate enhancer-target relationships. Motif enrichment further supported the involvement of drought-responsive regulatory programs, and hundreds of candidates overlapped rice STARR-seq enhancers. Together, these data define a drought-responsive atlas of candidate enhancer-like nascent transcription in rice and provide prioritized cis-regulatory candidates for mechanistic validation and crop improvement.
- organism: plant (other)
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: chromatin & epigenetic regulation
- approach: deep learning
- approach: statistical model
- Citations
- 0
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